Forecasting

The fuzzy time series model has become a research topic attracting attention because of its practical value in the field of time series forecasting, specifically, it is useful for time series with small observations or the one of strong fluctuations. This paper introduces a fuzzy time series model based on hedge algebra with a new formula for calculating forecasting values.

9p viengfa 28-10-2024 2 1   Download

Accurate daily load forecasting is critical for effective energy management planning. In this study, the article proposes a new method for daily load forecasting that takes advantage of load data and weather data over time in Tien Giang.

10p viengfa 28-10-2024 1 1   Download

Accurate forecasting of the electrical load is a critical element for grid operators to make well-informed decisions concerning electricity generation, transmission, and distribution. In this study, an Extreme Learning Machine (ELM) model was proposed and compared with four other machine learning models including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).

10p viengfa 28-10-2024 2 1   Download

This article conducts an exhaustive investigation into the utilization of machine learning (ML) methods for forecasting the maximum load capacity (MLC) of circular reinforced concrete columns (CRCC) using Fiber-Reinforced Polymer (FRP). Extreme Gradient Boosting (XGB) algorithm is combined with novel metaheuristic algorithms, namely Sailfish Optimizer and Aquila Optimizer, to fine-tune its hyperparameters.

18p viengfa 28-10-2024 2 2   Download

This paper is aimed to apply hybrid machine learning model namely GA-ANFIS, which is a combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA), for the prediction of total bearing capability of driven piles.

8p viengfa 28-10-2024 3 2   Download

This article uses Random Forest (RF) and k-fold cross-validation to predict the hourly count of rental bikes (cnt/h) in the city of Seoul (Korea) using information related to rental hour, temperature, humidity, wind speed, visibility, dewpoint, solar radiation, snowfall, and rainfall.

9p viengfa 28-10-2024 2 2   Download

In this study, we propose a machine learning technique for estimating the shear strength of CRC beams across a range of service periods. To do this, we gathered 158 CRC beam shear tests and used Artificial Neural Network (ANN) to create a forecast model for the considered output.

12p viengfa 28-10-2024 3 2   Download

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. This study applied the repeated KFold cross-validation technique with 10 folds on the training data set to make the simulation results more reliable and find a model with more general predictive power.

9p viengfa 28-10-2024 5 2   Download

This study proposes the application of Ensemble Decision Tree Boosted (EDT Boosted) model for forecasting the surface chloride concentration of marine concrete Cs. A database of 386 experimental results was collected from 17 different sources covering twelve variables was used to build and verify the predictive power of the EDT model.

12p viengfa 28-10-2024 5 2   Download

The results of this study would be useful in quickly and accurately predicting CPI to the management agencies, investors, construction contractors to pre-plan the construction investment costs. This will also help in suitably adjusting changing construction cost with time.

11p viengfa 28-10-2024 2 2   Download

Initial Public Offering (IPO) is considered a strategic decision of utmost importance for every business, especially companies that wish to list on the stock exchange. international. Using the Wilcoxon non-parametric test method, the study shows that IPO activities have a positive impact on the profits of businesses listed on the NASDAQ Global Select Market stock exchange in general and of VinFast in particular.

16p viling 11-10-2024 3 1   Download

This research paper focuses on the critical role of demand forecasting in FMCG, emphasizing the need for LSTM-based deep learning models to deal with demand uncertainty and improve predictive outcomes. Through this exploration, we aim to illuminate the link between demand forecasting and advanced deep learning, enabling FMCG companies to thrive in a highly dynamic business landscape.

8p vifilm 11-10-2024 2 1   Download

Consumer demand is an important factor in any business, especially in the food retail industry whose products are perishable and have a short life cycle. The daily demand for a food product is affected by external factors, such as seasonality, price reduction and holidays.

8p vifilm 11-10-2024 2 1   Download

This research introduces the application of such a model in Hai Phong City and identifies the challenges and solutions to improve the implementation of traffic demand forecasting models in Vietnam. We believe that these results will support policymakers and researchers with a basis for enhancing the effectiveness of urban transportation planning, management, and operation.

5p vibecca 01-10-2024 6 2   Download

This article presents research on the practical development, the impacts, and the application of Industry 4.0 technologies in the real estate market in Vietnam. Through this examination, it evaluates, forecasts, and recommends solutions to foster a healthy real estate market and improve the mechanisms of real estate market development in the foreseeable future.

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This study involves the application of MIKE-FLOOD to the Duc My Bridge within the Dinh River floodplain. The objective is to implement inundation assessment methodology and present a reliability analysis framework to investigate flood vulnerability through a real-world bridge case study."

17p vibecca 01-10-2024 2 1   Download

Saline intrusion is a big challenge for the Mekong Delta region, a negative factor that greatly affects water and food security. This paper presents a study to assess the trend of saline intrusion change in the 5 coastal sub–regions between the Tien and Hau rivers in the period 1997 to 2022.

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Japan International Cooperation Agency (JICA) and the Viet Nam Meteorological and Hydrological Administration (VNMHA) have implemented a technical cooperation project entitled “Project for Strengthening Capacity in Weather Forecasting and Flood Early Warning System” for more than 5 years from May 2018. In period 2 from April 2020 to the present, the project has achieved some outstanding achievements.

9p vibecca 01-10-2024 1 1   Download

Development of forecast guidance is one of main activities of Output 3 of the JICA Project to improve forecasting services of VNMHA. Maximum and minimum temperature guidance was developed for 63 cities up to 10 days ahead in the first phase of the Project. Development of precipitation guidance was the primary activity of Output 3 in the second phase of the Project.

19p vibecca 01-10-2024 1 1   Download

NCHMF and JICA team decided development of mobile services as an activity of the JICA Project. The mobile service system displays the data of Automatic Rain Gauge (ARG) stations, radars and meteorological satellites and the extreme weather warning messages disseminated from the system are aimed at users nationwide.

11p vibecca 01-10-2024 1 1   Download